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Burning fuels in power plants or motor vehicles emits carbon dioxide (CO2), which contributes to global warming. The table below displays CO2 emissions per person from countries with populations of at least 20 million. COUNTRY Co2 COUNTRY CO2 COUNTRY Co2 Algeria Argentina Australia Bangladesh Brazil Canada China Colombia Congo Egypt Ethiopia France Germany Ghana India Indonesia 2.6 3.6 18.4 0.3 6.0 2.9 Poland Romania Russia Saudi Arabia South Africa Iran Iraq Italy Japan Kenya Korea, North Korea, South Malaysia Mexico Morocco Myanmar Nepal Nigeria Pakistan 4.2 10.8 13.8 7.0 9.5 0.3 17.0 3.9 1.3 0.2 2.0 in 0.3 0.1 9.3 Sudan Tanzania Thailand 3.7 1.4 Turkey 0.2 0.1 0.4 0.8 Ukraine United Kingdom United States Uzbekistan Venezuela Vietnam 6.3 8.8 19.6 4.2 5.4 6.2 9.9 0.3 eru Philippines 0.9

a) Why do you think we choose to measure emissions per person rather than total CO2 emissions for each country?

b) Make a stemplot to display the data.

c) Describe shape, center, spread of the distribution

d) Use the 1.5xIQR rule to determine the possible outliers. List the outliers. Show all work.

e) No visually, using the stemplot you created, what are the additional outlier(s)? Discusses why you chose these outlier(s)

f) In this case, is it better to use the 1.5x IQR Rule, or to visually look at the data to select outliers?

math   Statistics-And-Probability   
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(a) Emissions are measured per person because, other things equal, more populous countries would naturally be expected to have higher levels of emissions Total CO2 emissions for each country would be influenced by the population of each country. So, countries with higher populations would have higher total CO2 emissions. To mitigate the effect of larger populations, we divide the total emissions by the population, so the average per person is (or should be) uninfluenced by the size of the population. Stem and Leaf Plot: Stem Leaf 0000 0 0 0 0 0 00 0 0 1111111222 3 3 3 3 3 3445 566677778999 103789Histogram of CO2 Normal 16T 14 12 10- Mean 4.727 StDev 4.940 1015 20 CO2 (c) The graph indicates that the histogram is positively skewed and has outliers. The vertical bar far from the diagram indicates the points of outliers. The vertical bars far from the other set of vertical bars, the points indicate that they are outliers. Therefore, the data set contains outliers. (d) An outlier in a distribution is a number that is more than 1.5 times the length of the box away from either the lower or upper quartiles. Speci?cally, if a number is less than G1 - 1.5xIQR or greater than 03+ 1.5xIQR, then it is an outlier.the interquartile range (IOR) is a measure of statistical dispersion, being equal to the difference between the third quartile (Q3) and first quartile (Q1), that is, IOR 03 Q1. Lower fence: -8.72:5 Upper fence: 17.075 HERE OUTLIERS ARE: 18.4, 19.6 (f) Spread measures like the IQR tell us how far a typical value could be from the average, so anything much more than the typical distance can be identified 1.5xlOR is one of the most straightforward They help us measure how uncertain we are about our central values. For skew, avoid the whole mess and use the IQR

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